This work presents the use of laser diode in the fiber distributed data interface FDDI networks. FDDI uses optical fiber as a transmission media. This solves the problems resulted from the EMI, and noise. In addition it increases the security of transmission. A network with a ring topology consists of three computers was designed and implemented. The timed token protocol was used to achieve and control the process of communication over the ring. Nonreturn to zero inversion (NRZI) modulation was carried out as a part of the physical (PHY) sublayer. The optical system consists of a laser diode with wavelength of 820 nm and 2.5 mW maximum output power as a source, optical fiber as a channel, and positive intrinsic negative (PIN) photodiode with maximum responsivity at wavelength of 820 nm as a detector. Practical tests were carried out on the laser diode showed that the output characteristics and spectral characteristics of the laser diode depend largely on the drive current. The maximum separation distance between successive stations in the ring was 5.4 km. From the performance tests, it was concluded that the maximum throughput and maximum access delay are directly proportional to length of the transmitted information. A trade off between the transmitted information length and the maximum access delay is needed.
The physical and elastic characteristics of rocks determine rock strengths in general. Rock strength is frequently assessed using porosity well logs such as neutron and sonic logs. The essential criteria for estimating rock mechanic parameters in petroleum engineering research are uniaxial compressive strength and elastic modulus. Indirect estimation using well-log data is necessary to measure these variables. This study attempts to create a single regression model that can accurately forecast rock mechanic characteristics for the Harth Carbonate Formation in the Fauqi oil field. According to the findings of this study, petrophysical parameters are reliable indexes for determining rock mechanical properties having good performance p
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Precise forecasting of pore pressures is crucial for efficiently planning and drilling oil and gas wells. It reduces expenses and saves time while preventing drilling complications. Since direct measurement of pore pressure in wellbores is costly and time-intensive, the ability to estimate it using empirical or machine learning models is beneficial. The present study aims to predict pore pressure using artificial neural network. The building and testing of artificial neural network are based on the data from five oil fields and several formations. The artificial neural network model is built using a measured dataset consisting of 77 data points of Pore pressure obtained from the modular formation dynamics tester. The input variables
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Tight reservoirs have attracted the interest of the oil industry in recent years according to its significant impact on the global oil product. Several challenges are present when producing from these reservoirs due to its low to extra low permeability and very narrow pore throat radius. Development strategy selection for these reservoirs such as horizontal well placement, hydraulic fracture design, well completion, and smart production program, wellbore stability all need accurate characterizations of geomechanical parameters for these reservoirs. Geomechanical properties, including uniaxial compressive strength (UCS), static Young’s modulus (Es), and Poisson’s ratio (υs), were measured experimentally using both static and dynamic met
... Show MoreThe two parameters of Exponential-Rayleigh distribution were estimated using the maximum likelihood estimation method (MLE) for progressively censoring data. To find estimated values for these two scale parameters using real data for COVID-19 which was taken from the Iraqi Ministry of Health and Environment, AL-Karkh General Hospital. Then the Chi-square test was utilized to determine if the sample (data) corresponded with the Exponential-Rayleigh distribution (ER). Employing the nonlinear membership function (s-function) to find fuzzy numbers for these parameters estimators. Then utilizing the ranking function transforms the fuzzy numbers into crisp numbers. Finally, using mean square error (MSE) to compare the outcomes of the survival
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Background: Glass ionomer restorations are widely employed in the field of pediatric dentistry. There is a constant demand for a durable restoration that remains functional until exfoliation. This study aimed to measure and compare the effect of a novel coating material (EQUIA Forte Coat) on the microleakage of glass hybrid restoration (EQUIA Forte HT) in primary teeth. Material and method: Thirty cavitated (class-II) primary molars were allocated randomly into two groups based on the coat application; uncoated (control) and coated group (experimental). Cavities were prepared by the use of a ceramic bur (CeraBur) and restored with EQUIA Forte HT with or without applying a protective coat (EQUIA Forte Coat). Samples went through the
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Suffer most of the facilities of the high cost of inventory , which affects the high cost of the product and thus affects many administrative decisions , as well as suffer the facilities of the systems developed by the provisions of inventory control , and this problem is exacerbated in the construction sector where the inventory in the form of Construction spin of the Year for another it becomes difficult to control the cost effectively , and is the research problem in question follows: What are the implications of the use of the system in time inventory accounting system for the contracting company does kills Alrkaah to the provisions of the cost of inventory and what is the optimal approach to inventory control ? Find assumed
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Background: Glass ionomer restorations are widely employed in the field of pediatric dentistry. There is a constant demand for a durable restoration that remains functional until exfoliation. This study aimed to measure and compare the effect of a novel coating material (EQUIA Forte Coat) on the microleakage of glass hybrid restoration (EQUIA Forte HT) in primary teeth. Material and method: Thirty cavitated (class-II) primary molars were allocated randomly into two groups based on the coat application; uncoated (control) and coated group (experimental). Cavities were prepared by the use of a ceramic bur (CeraBur) and restored with EQUIA Forte HT with or without applying a protective coat (EQUIA Forte Coat). Samples went through the therm
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